永磁直线电机伺服系统智能增量滑模控制

发布时间：2018-01-29 16:01

本文关键词： 永磁直线同步电机增量滑模控制智能增量滑模控制抖振鲁棒性　出处：《沈阳工业大学》2017年硕士论文　论文类型：学位论文

【摘要】：直线电机伺服系统作为衡量制造业水平的重要标志,需要满足高速度高精度的需求。永磁直线同步电机(PMLSM)具有高能量密度、高推力-体积比等优点,广泛应用于半导体生产、水下探测、机器人控制、XY平台驱动等工业领域。针对PMLSM伺服系统易受参数变化、外部扰动、端部效应等不确定性因素的影响,提出了增量滑模控制(ISMC)、自适应增量滑模控制(AISMC)和智能增量滑模控制(IISMC)来提高系统鲁棒性,削弱抖振,进而改善系统的跟踪精度。首先介绍PMLSM的结构和工作原理,建立了PMLSM的数学模型;接着对离散滑模控制(DSMC)方法的原理和设计方法进行了介绍。为了削弱抖振现象,同时增强系统的鲁棒性,在DSMC基础上,将系统先前的控制动作和状态考虑进滑模面和控制律的设计中,并选用饱和函数作为切换函数,提出了ISMC方法,设计了基于ISMC的PMLSM伺服系统。为了消除切换函数增益的大小对抖振和响应速度的不利影响,将自适应控制和ISMC相结合,提出AISMC方法,采用自适应律实时调整切换函数的增益,设计了基于AISMC的PMLSM伺服系统。为了进一步抑制不确定因素对系统的干扰,提高系统的跟踪精度,设计了基于IISMC的PMLSM伺服系统。采用小波神经网络(WNN)对不确定因素进行实时观测,对控制律进行补偿。考虑粒子的最差位置,设计了改进的粒子群算法(IPSO)对WNN的学习率进行实时调整,增强WNN的学习能力。最后针对所提出的ISMC、AISMC、IISMC方法,建立基于这些方法的PMLSM伺服系统仿真模型,通过仿真结果分析,验证了所提出的方法可以有效削弱抖振,增强系统的鲁棒性,提高系统的控制精度,对比表明IISMC方法具有最好的控制性能。
[Abstract]:As an important symbol to measure the level of manufacturing industry, linear motor servo system needs to meet the demand of high speed and high precision. PMLSM (permanent Magnet Linear synchronous Motor) has high energy density. The advantages of high thrust-volume ratio are widely used in semiconductor production underwater detection robot control XY platform drive and other industrial fields. The PMLSM servo system is vulnerable to parameter changes and external disturbances. An incremental sliding mode control (ISMCC) is proposed for the effect of the end effect and other uncertain factors. Adaptive incremental sliding mode control (AISMC) and intelligent incremental sliding mode control (IISMCC) are used to improve system robustness and weaken buffeting. Then the tracking accuracy of the system is improved. Firstly, the structure and working principle of PMLSM are introduced, and the mathematical model of PMLSM is established. Then the principle and design method of discrete sliding mode control (DSMC) method are introduced. In order to weaken the chattering phenomenon and enhance the robustness of the system, the system is based on DSMC. The previous control actions and states of the system are considered in the design of sliding mode surface and control law, and the saturation function is selected as the switching function, and the ISMC method is proposed. A PMLSM servo system based on ISMC is designed. In order to eliminate the adverse effect of the gain of switching function on buffeting and response speed, adaptive control is combined with ISMC. The AISMC method is proposed to adjust the gain of switching function in real time by using adaptive law, and a PMLSM servo system based on AISMC is designed. In order to further suppress the disturbance of uncertain factors to the system. To improve the tracking accuracy of the system, a PMLSM servo system based on IISMC is designed. The wavelet neural network (WNN) is used to observe the uncertain factors in real time. Considering the worst position of particle, an improved particle swarm optimization algorithm (PSO) is designed to adjust the learning rate of WNN in real time. Finally, the simulation model of PMLSM servo system based on these methods is established, and the simulation results are analyzed. It is verified that the proposed method can effectively weaken buffeting, enhance the robustness of the system and improve the control accuracy of the system. The comparison shows that the IISMC method has the best control performance.
【学位授予单位】：沈阳工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM359.4;TM921.541

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